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MT23 Education Newsletter

Stay up to date with news from the Personalised Medicine world!

Welcome back to the second edition of our Education Newsletters. Hope you all have an enjoyable winter break and see you in the New Year! As always, please reach out to us if you have a story you'd like us to include in the next edition.


New in Personalised Med

“Anthrobots”: The biological robots that could help repair brain tissue

A spheroid-shaped multicellular biological structure, termed “anthrobot”, has been developed by a team of scientists from human lung (tracheal) cells. These structures have cilia and are mobile, and have been shown to be able to traverse sheets of human neural tissues and induce repair in vitro. While this research remains in preliminary stages, it has the potential to greatly impact regenerative medicine. 


Read more about this here.

Google's new healthcare generative AI model

Google has recently launched a new specialised generative AI model - MedLM. They claim that the AI model is capable of performing complex medical decision making, achieving “85% accuracy” on the US Medical Licencing Exam (a test taken by doctors in the US to be certified) according to Google. Pre-clinical and clinical uses of the model have been described, including expediting drug development and working as a chatbot to provide patient care advice respectively. 

Clinical trial launched in Oxford testing an mRNA vaccine for HPV-16 positive head and neck cancers

A vaccine trial has been launched by Oxford University Hospitals, focussed on patients with advanced metastatic head and neck cancers. This is the first mRNA cancer vaccine trial to open in Oxford. The trial aims to assess if the vaccine can improve patient response to immunotherapy. 


Read more about this here.


Deep Dive: Omics

With advancements in techniques for biological investigation, development of high-throughput technology, and the expansion of bioinformatics and AI-based analysis of health data, “Omic” strategies have become increasingly central to personalised medicine.  Omics refer to the large-scale analysis of properties of an individual cell or organism. This can occur at different levels of gene expression, for example genomics, transcriptomics, proteomics and epigenomics; at a functional level, for example metabolomics, interactomics and pharmacogenomics; and at a cellular level, for example immunomics and microbiomics.


Many omic strategies are already in use in the clinic. For example, MALDI-TOF-MS (Matrix-Assisted Laser Desorption Ionisation-Time-Of-Flight Mass Spectroscopy) is a laboratory technique used to characterise the bacterial proteosome. This allows for rapid identification of bacterial species present within a sample, so a more narrow spectrum antibiotics can be prescribed for effective treatment with reduced impact on the rest of the microbiome. Genomic analysis can be used to identify polymorphisms that predispose an individual to developing a disease – for example, certain HLA polymorphisms are associated with increased risk of autoimmune conditions.


Although newer technologies like next-generation sequencing are comparatively cheaper than previously used methods like Sanger sequencing, molecular omic strategies remain quite expensive and are unlikely to come into widespread use in clinics in the immediate future. Further, identifying disease factors through these techniques is reliant on collecting data from a large sample size, and the scope and reach of this is again limited by the resources available. For example, many GWAS (genome-wide association studies) conducted so far have been on data highly skewed towards the Caucasian population. Analysis of data from a diverse population group is important to draw conclusions that can be used clinically across the globe and for individuals with different ethnic backgrounds. Another consideration for handling such large amounts of data from different individuals is the issues of data sharing and confidentiality.


Infographic of the Month

Oxford led study shows that increased microbiome diversity can be protective against colonisation by pathogens due to nutrient blocking. A more varied microbiome composition results in a greater range of nutrients being consumed by different microbes, reducing the probability of colonisation by pathogens.


Source: Frances Spragge et al., Microbiome diversity protects against pathogens by nutrient blocking. Science 382, eadj3502(2023).DOI:10.1126/science.adj3502

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